Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/75570
Title: Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet
Authors: Dominguez, Oscar
Juan, Angel A.
Barrios, Barry
Faulin, Javier
Agustin, Alba
Keywords: Heterogeneous Vehicle Routing Problem
Two-Dimensional Bin Packing Problem
Randomized Heuristics
Multi-Start Algorithms
Issue Date: 2016
Journal: Annals of Operations Research 
Conference: Operations Research Peripatetic Postgraduate Program Conference (ORP3) 
Abstract: This paper discusses the two-dimensional loading capacitated vehicle routing problem (2L-CVRP) with heterogeneous fleet (2L-HFVRP). The 2L-CVRP can be found in many real-life situations related to the transportation of voluminous items where two-dimensional packing restrictions have to be considered, e.g.: transportation of heavy machinery, forklifts, professional cleaning equipment, etc. Here, we also consider a heterogeneous fleet of vehicles, comprising units of different capacities, sizes and fixed/variable costs. Despite the fact that heterogeneous fleets are quite ubiquitous in real-life scenarios, there is a lack of publications in the literature discussing the 2L-HFVRP. In particular, to the best of our knowledge no previous work discusses the non-oriented 2L-HFVRP, in which items are allowed to be rotated during the truck-loading process. After describing and motivating the problem, a literature review on related work is performed. Then, a multi-start algorithm based on biased randomization of routing and packing heuristics is proposed. A set of computational experiments contribute to illustrate the scope of our approach, as well as to show its efficiency.
URI: http://hdl.handle.net/10553/75570
ISSN: 0254-5330
DOI: 10.1007/s10479-014-1551-4
Source: Annals of Operations Research [ISSN 0254-5330], v. 236 (2), p. 383-404, (Enero 2016)
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